AIBECS functions

load

Returns wet3d, grd, and T (in that order) from FigShare repository.

vector_of_depths(wet3d, grd)

Returns the vector of depths of the center of wet boxes.

number_of_wet_boxes(wet3d)

Returns the number of wet grid boxes.

indices_of_wet_boxes(wet3d)

Returns the vector of the indices of wet grid boxes.

add_parameter!(t::DataFrame, args...; kwargs...)

Adds a parameter to the parameters table t. If keyword argument optimizable = false, then observation mean and variance are set to NaN. Otherwise, these are set to keyword arguments mean_obs (and variance_obs) if supplied, or to quantity (and its square), after converting it to the preferred unit and stripping it of said unit if not. Example: TODO Note for future edit of the docs: Don't repeat yourself between add and new param functions

initialize_Parameters_type(t, PName="Parameters")

Generate the type called after PName and all its functionality with it. It is recommended to use upper camel case for PName as for all user-defined Julia types. PName defaults to "Parameters".

For example, use

julia> initialize_Parameters_type(t) # creates Parameters

or

julia> initialize_Parameters_type(t, "MyPara") # creates MyPara

F, ∇ₓF = state_function_and_Jacobian(Ts, Gs, nb)

Returns the state function F and its jacobian, ∇ₓF.

prob = SteadyStateProblem(F, ∇ₓF, x, p)

Returns the SteadyStateProblem defined by F(x,p)=0.